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Our latest news and articles about physics and bio inspired computing, cryptography, future technologies, innovations, curated from our team, updated daily. Make sure to visit our page periodically for the latest updates.

Meet the 2022-23 Accenture Fellows

Launched in October 2020, the MIT and Accenture Convergence Initiative for Industry and Technology underscores the ways in which industry and technology can collaborate to spur innovation. The five-year initiative aims to achieve its mission through research, education, and fellowships. To that end,…

Pursuing a practical approach to research

Koroush Shirvan, the John Clark Hardwick Career Development Professor in the Department of Nuclear Science and Engineering (NSE), knows that the nuclear industry has traditionally been wary of innovations until they are shown to have proven utility. As a result, he has relentlessly focused on practi…

Large language models help decipher clinical notes

Electronic health records (EHRs) need a new public relations manager. Ten years ago, the U.S. government passed a law that required hospitals to digitize their health records with the intent of improving and streamlining care. The enormous amount of information in these now-digital records could be …

Ushering in a new era of computing

As a graduate student doing his master’s thesis on speech recognition at the MIT AI Lab (now the MIT Computer Science and Artificial Intelligence Laboratory), Dan Huttenlocher worked closely with Professor Victor Zue. Well known for pioneering the development of systems that enable an user to intera…

Busy GPUs: Sampling and pipelining method speeds up deep learning on large graphs

Graphs, a potentially extensive web of nodes connected by edges, can be used to express and interrogate relationships between data, like social connections, financial transactions, traffic, energy grids, and molecular interactions. As researchers collect more data and build out these graphical pictu…

Breaking the scaling limits of analog computing

As machine-learning models become larger and more complex, they require faster and more energy-efficient hardware to perform computations. Conventional digital computers are struggling to keep up. An analog optical neural network could perform the same tasks as a digital one, such as image classific…

Teresa Gao named 2024 Mitchell Scholar

MIT senior Teresa Gao has been named one of the 12 winners of the George J. Mitchell Scholarship’s Class of 2024. After graduating next spring with a double major in computer science and engineering as well as brain and cognitive sciences, she will study augmented and virtual reality at Trinity Coll…

A simpler path to better computer vision

Before a machine-learning model can complete a task, such as identifying cancer in medical images, the model must be trained. Training image classification models typically involves showing the model millions of example images gathered into a massive dataset. However, using real image data can raise…

A far-sighted approach to machine learning

Picture two teams squaring off on a football field. The players can cooperate to achieve an objective, and compete against other players with conflicting interests. That’s how the game works. Creating artificial intelligence agents that can learn to compete and cooperate as effectively as humans rem…

Solving brain dynamics gives rise to flexible machine-learning models

Last year, MIT researchers announced that they had built “liquid” neural networks, inspired by the brains of small species: a class of flexible, robust machine learning models that learn on the job and can adapt to changing conditions, for real-world safety-critical tasks, like driving and flying. T…

Ensuring AI works with the right dose of curiosity

It’s a dilemma as old as time. Friday night has rolled around, and you’re trying to pick a restaurant for dinner. Should you visit your most beloved watering hole or try a new establishment, in the hopes of discovering something superior? Potentially, but that curiosity comes with a risk: If you exp…

A whole new world of learning via MIT OpenCourseWare videos

Like millions of others during the global Covid-19 lockdowns, Emmanuel Kasigazi, an entrepreneur from Uganda, turned to YouTube to pass the time. But he wasn’t following an influencer or watching music videos. A lifelong learner, Kasigazi was scouring the video-sharing platform for educational resou…

Video on the record

Among the Pulitzer Prizes awarded in 2021 was a citation for a teenager who changed history with her cell phone. The Pulitzer committee acknowledged Darnella Frazier “for courageously recording the murder of George Floyd, a video that spurred protests against police brutality around the world, highl…

In machine learning, synthetic data can offer real performance improvements

Teaching a machine to recognize human actions has many potential applications, such as automatically detecting workers who fall at a construction site or enabling a smart home robot to interpret a user’s gestures. To do this, researchers train machine-learning models using vast datasets of video cli…

Study urges caution when comparing neural networks to the brain

Neural networks, a type of computing system loosely modeled on the organization of the human brain, form the basis of many artificial intelligence systems for applications such speech recognition, computer vision, and medical image analysis. In the field of neuroscience, researchers often use neural…

Machine learning facilitates “turbulence tracking” in fusion reactors

Fusion, which promises practically unlimited, carbon-free energy using the same processes that power the sun, is at the heart of a worldwide research effort that could help mitigate climate change. A multidisciplinary team of researchers is now bringing tools and insights from machine learning to ai…

Using sound to model the world

Imagine the booming chords from a pipe organ echoing through the cavernous sanctuary of a massive, stone cathedral. The sound a cathedral-goer will hear is affected by many factors, including the location of the organ, where the listener is standing, whether any columns, pews, or other obstacles sta…

3 Questions: How AI image generators could help robots

AI image generators, which create fantastical sights at the intersection of dreams and reality, bubble up on every corner of the web. Their entertainment value is demonstrated by an ever-expanding treasure trove of whimsical and random images serving as indirect portals to the brains of human design…

Deep learning with light

Ask a smart home device for the weather forecast, and it takes several seconds for the device to respond. One reason this latency occurs is because connected devices don’t have enough memory or power to store and run the enormous machine-learning models needed for the device to understand what a use…

The science of strength: How data analytics is transforming college basketball

In the 1990s, if you suggested that the corner three-pointer was the best shot in basketball, you might have been laughed out of the gym. The game was still dominated largely by a fleet of seven-foot centers, most of whom couldn’t shoot from more than a few feet out from the basket. Even the game’s&…

Study finds the risks of sharing health care data are low

In recent years, scientists have made great strides in their ability to develop artificial intelligence algorithms that can analyze patient data and come up with new ways to diagnose disease or predict which treatments work best for different patients. The success of those algorithms depends on acce…

Learning on the edge

Microcontrollers, miniature computers that can run simple commands, are the basis for billions of connected devices, from internet-of-things (IoT) devices to sensors in automobiles. But cheap, low-power microcontrollers have extremely limited memory and no operating system, making it challenging to …

Wiggling toward bio-inspired machine intelligence

Juncal Arbelaiz Mugica is a native of Spain, where octopus is a common menu item. However, Arbelaiz appreciates octopus and similar creatures in a different way, with her research into soft-robotics theory.  More than half of an octopus’ nerves are distributed through its eight arms, each of which h…

New program to support translational research in AI, data science, and machine learning

The MIT School of Engineering and Pillar VC today announced the MIT-Pillar AI Collective, a one-year pilot program funded by a gift from Pillar VC that will provide seed grants for projects in artificial intelligence, machine learning, and data science with the goal of supporting translational resea…

Neurodegenerative disease can progress in newly identified patterns

Neurodegenerative diseases — like amyotrophic lateral sclerosis (ALS, or Lou Gehrig’s disease), Alzheimer’s, and Parkinson’s — are complicated, chronic ailments that can present with a variety of symptoms, worsen at different rates, and have many underlying genetic and environmental causes, so…

Q&A: Global challenges surrounding the deployment of AI

The AI Policy Forum (AIPF) is an initiative of the MIT Schwarzman College of Computing to move the global conversation about the impact of artificial intelligence from principles to practical policy implementation. Formed in late 2020, AIPF brings together leaders in government, business, and academ…

Understanding reality through algorithms

Although Fernanda De La Torre still has several years left in her graduate studies, she’s already dreaming big when it comes to what the future has in store for her. “I dream of opening up a school one day where I could bring this world of understanding of cognition and perception into places that w…

In-home wireless device tracks disease progression in Parkinson’s patients

Parkinson’s disease is the fastest-growing neurological disease, now affecting more than 10 million people worldwide, yet clinicians still face huge challenges in tracking its severity and progression. Clinicians typically evaluate patients by testing their motor skills and cognitive functions durin…

Empowering Cambridge youth through data activism

For over 40 years, the Mayor’s Summer Youth Employment Program (MSYEP, or the Mayor’s Program) in Cambridge, Massachusetts, has been providing teenagers with their first work experience, but 2022 brought a new offering. Collaborating with MIT’s Personal Robots research group (PRG) and Responsi…

Protecting maternal health in Rwanda

The world is facing a maternal health crisis. According to the World Health Organization, approximately 810 women die each day due to preventable causes related to pregnancy and childbirth. Two-thirds of these deaths occur in sub-Saharan Africa. In Rwanda, one of the leading causes of maternal morta…

Computing for the health of the planet

The health of the planet is one of the most important challenges facing humankind today. From climate change to unsafe levels of air and water pollution to coastal and agricultural land erosion, a number of serious challenges threaten human and ecosystem health. Ensuring the health and safety of our…

AI system makes models like DALL-E 2 more creative

The internet had a collective feel-good moment with the introduction of DALL-E, an artificial intelligence-based image generator inspired by artist Salvador Dali and the lovable robot WALL-E that uses natural language to produce whatever mysterious and beautiful image your heart desires. Seeing type…

Collaborative machine learning that preserves privacy

Training a machine-learning model to effectively perform a task, such as image classification, involves showing the model thousands, millions, or even billions of example images. Gathering such enormous datasets can be especially challenging when privacy is a concern, such as with medical images. Re…

Analyzing the potential of AlphaFold in drug discovery

Over the past few decades, very few new antibiotics have been developed, largely because current methods for screening potential drugs are prohibitively expensive and time-consuming. One promising new strategy is to use computational models, which offer a potentially faster and cheaper way to identi…

Using machine learning to identify undiagnosable cancers

The first step in choosing the appropriate treatment for a cancer patient is to identify their specific type of cancer, including determining the primary site — the organ or part of the body where the cancer begins. In rare cases, the origin of a cancer cannot be determined, even with extensive test…

AI that can learn the patterns of human language

Human languages are notoriously complex, and linguists have long thought it would be impossible to teach a machine how to analyze speech sounds and word structures in the way human investigators do. But researchers at MIT, Cornell University, and McGill University have taken a step in this direction…

Taking a magnifying glass to data center operations

When the MIT Lincoln Laboratory Supercomputing Center (LLSC) unveiled its TX-GAIA supercomputer in 2019, it provided the MIT community a powerful new resource for applying artificial intelligence to their research. Anyone at MIT can submit a job to the system, which churns through trillions of opera…

Building better batteries, faster

To help combat climate change, many car manufacturers are racing to add more electric vehicles in their lineups. But to convince prospective buyers, manufacturers need to improve how far these cars can go on a single charge. One of their main challenges? Figuring out how to make extremely powerful b…

Artificial intelligence model can detect Parkinson’s from breathing patterns

Parkinson’s disease is notoriously difficult to diagnose as it relies primarily on the appearance of motor symptoms such as tremors, stiffness, and slowness, but these symptoms often appear several years after the disease onset. Now, Dina Katabi, the Thuan (1990) and Nicole Pham Professor in the Dep…

New programmable materials can sense their own movements

MIT researchers have developed a method for 3D printing materials with tunable mechanical properties, that sense how they are moving and interacting with the environment. The researchers create these sensing structures using just one material and a single run on a 3D printer. To accomplish this, the…

Caspar Hare, Georgia Perakis named associate deans of Social and Ethical Responsibilities of Computing

Caspar Hare and Georgia Perakis have been appointed the new associate deans of the Social and Ethical Responsibilities of Computing (SERC), a cross-cutting initiative in the MIT Stephen A. Schwarzman College of Computing. Their new roles will take effect on Sept. 1. “Infusing social and ethical aspe…

3 Questions: Amar Gupta on an integrated approach to enhanced health-care delivery

Covid-19 was somewhat of a metaverse itself. Many of our domains turned digital — with much attention toward one emerging space: virtual care. The pandemic exacerbated the difficulties of providing appropriate medical board oversight to ensure proper standard of services for patients. MIT researcher…

Leveraging computational tools to enhance product design

As an undergraduate at MIT, Jana Saadi had to find a way to fulfill her humanities class requirements. Little did she know that her decision would heavily shape her academic career. On a whim, Saadi had joined a friend in a class offered through MIT D-Lab, a project-based program aimed at helping po…

Solving a longstanding conundrum in heat transfer

It is a problem that has beguiled scientists for a century. But, buoyed by a $625,000 Distinguished Early Career Award from the U.S. Department of Energy (DoE), Matteo Bucci, an associate professor in the Department of Nuclear Science and Engineering (NSE), hopes to be close to an answer. Tackling t…

Physics Inspired Computation — Solving Constraint Satisfaction Problems with Physics

Computationally challenging optimisation problems have always been of special interest by various researchers around the globe. This is primarily due to them often having a very high dimensional search space, or having highly complex and non-linear objective functions at their co…

Using Bio-Inspired Computing to Efficiently Solving SAT Problems

With Moore’s law coming to an end, and, with it, the digital age, alternative novel computing systems have to be explored. Physical systems and processes, just like biological ones, can inspire the design of computer algorithms. Early ideas The ideas behind biological computing trace back to 1936 an…

Is diversity the key to collaboration? New AI research suggests so

As artificial intelligence gets better at performing tasks once solely in the hands of humans, like driving cars, many see teaming intelligence as a next frontier. In this future, humans and AI are true partners in high-stakes jobs, such as performing complex surgery or defending from missiles. But …

In bias we trust?

When the stakes are high, machine-learning models are sometimes used to aid human decision-makers. For instance, a model could predict which law school applicants are most likely to pass the bar exam to help an admissions officer determine which students should be accepted. These models often have m…

Inaugural Day of AI brings new digital literacy to classrooms worldwide

The first annual Day of AI on Friday, May 13 introduced artificial intelligence literacy to classrooms all over the world. An initiative of MIT Responsible AI for Social Empowerment and Education (RAISE), Day of AI is an opportunity for teachers to introduce K-12 students of all backgrounds to artif…

Hallucinating to better text translation

As babies, we babble and imitate our way to learning languages. We don’t start off reading raw text, which requires fundamental knowledge and understanding about the world, as well as the advanced ability to interpret and infer descriptions and relationships. Rather, humans begin our language journe…

Collin Stultz named co-director and MIT lead of the Harvard-MIT Program in Health Sciences and Technology

Collin M. Stultz, the Nina T. and Robert H. Rubin Professor in Medical Engineering and Science at MIT, has been named co-director of the Harvard-MIT Program in Health Sciences and Technology (HST), and associate director of MIT’s Institute for Medical Engineering and Science (IMES), effective June 1…

Student-powered machine learning

From their early days at MIT, and even before, Emma Liu ’22, MNG ’22, Yo-whan “John” Kim ’22, MNG ’22, and Clemente Ocejo ’21, MNG ’22 knew they wanted to perform computational research and explore artificial intelligence and machine learning. “Since high school, …

Engineers build LEGO-like artificial intelligence chip

Imagine a more sustainable future, where cellphones, smartwatches, and other wearable devices don’t have to be shelved or discarded for a newer model. Instead, they could be upgraded with the latest sensors and processors that would snap onto a device’s internal chip — like LEGO bricks incorporated …

Artificial neural networks model face processing in autism

Many of us easily recognize emotions expressed in others’ faces. A smile may mean happiness, while a frown may indicate anger. Autistic people often have a more difficult time with this task. It’s unclear why. But new research, published June 15 in The Journal of Neuroscience, sheds light on the inn…

Seeing the whole from some of the parts

Upon looking at photographs and drawing on their past experiences, humans can often perceive depth in pictures that are, themselves, perfectly flat. However, getting computers to do the same thing has proved quite challenging. The problem is difficult for several reasons, one being that information …

Researchers release open-source photorealistic simulator for autonomous driving

Hyper-realistic virtual worlds have been heralded as the best driving schools for autonomous vehicles (AVs), since they’ve proven fruitful test beds for safely trying out dangerous driving scenarios. Tesla, Waymo, and other self-driving companies all rely heavily on data to enable expensive and prop…

Robots play with play dough

The inner child in many of us feels an overwhelming sense of joy when stumbling across a pile of the fluorescent, rubbery mixture of water, salt, and flour that put goo on the map: play dough. (Even if this happens rarely in adulthood.) While manipulating play dough is fun and easy for 2-year-olds, …

Taking the guesswork out of dental care with artificial intelligence

When you picture a hospital radiologist, you might think of a specialist who sits in a dark room and spends hours poring over X-rays to make diagnoses. Contrast that with your dentist, who in addition to interpreting X-rays must also perform surgery, manage staff, communicate with patients, and run …

Exploring emerging topics in artificial intelligence policy

Members of the public sector, private sector, and academia convened for the second AI Policy Forum Symposium last month to explore critical directions and questions posed by artificial intelligence in our economies and societies. The virtual event, hosted by the AI Policy Forum (AIPF) — an undertaki…

Building explainability into the components of machine-learning models

Explanation methods that help users understand and trust machine-learning models often describe how much certain features used in the model contribute to its prediction. For example, if a model predicts a patient’s risk of developing cardiac disease, a physician might want to know how strongly the p…

Startup lets doctors classify skin conditions with the snap of a picture

At the age of 22, when Susan Conover wanted to get a strange-looking mole checked out, she was told it would take three months to see a dermatologist. When the mole was finally removed and biopsied, doctors determined it was cancerous. At the time, no one could be sure the cancer hadn’t spread to ot…

Smart textiles sense how their users are moving

Using a novel fabrication process, MIT researchers have produced smart textiles that snugly conform to the body so they can sense the wearer’s posture and motions. By incorporating a special type of plastic yarn and using heat to slightly melt it — a process called thermoforming — the researchers we…

Artificial intelligence model finds potential drug molecules a thousand times faster

The entirety of the known universe is teeming with an infinite number of molecules. But what fraction of these molecules have potential drug-like traits that can be used to develop life-saving drug treatments? Millions? Billions? Trillions? The answer: novemdecillion, or 1060. This gargantuan number…

Teaching AI to ask clinical questions

Physicians often query a patient’s electronic health record for information that helps them make treatment decisions, but the cumbersome nature of these records hampers the process. Research has shown that even when a doctor has been trained to use an electronic health record (EHR), finding an answe…

A technique to improve both fairness and accuracy in artificial intelligence

For workers who use machine-learning models to help them make decisions, knowing when to trust a model’s predictions is not always an easy task, especially since these models are often so complex that their inner workings remain a mystery. Users sometimes employ a technique, known as selective regre…

Explained: How to tell if artificial intelligence is working the way we want it to

About a decade ago, deep-learning models started achieving superhuman results on all sorts of tasks, from beating world-champion board game players to outperforming doctors at diagnosing breast cancer. These powerful deep-learning models are usually based on artificial neural networks, which were fi…

New hardware offers faster computation for artificial intelligence, with much less energy

As scientists push the boundaries of machine learning, the amount of time, energy, and money required to train increasingly complex neural network models is skyrocketing. A new area of artificial intelligence called analog deep learning promises faster computation with a fraction of the energy usage…

Using artificial intelligence to control digital manufacturing

Scientists and engineers are constantly developing new materials with unique properties that can be used for 3D printing, but figuring out how to print with these materials can be a complex, costly conundrum. Often, an expert operator must use manual trial-and-error — possibly making thousands of pr…

Why it’s a problem that pulse oximeters don’t work as well on patients of color

Pulse oximetry is a noninvasive test that measures the oxygen saturation level in a patient’s blood, and it has become an important tool for monitoring many patients, including those with Covid-19. But new research links faulty readings from pulse oximeters with racial disparities in health outcomes…

New algorithm aces university math course questions

Multivariable calculus, differential equations, linear algebra — topics that many MIT students can ace without breaking a sweat — have consistently stumped machine learning models. The best models have only been able to answer elementary or high school-level math questions, and they don’t always fin…

Stanford AI Lab Papers at ICCV 2021

The International Conference on Computer Vision (ICCV 2021) will be hosted virtually next week. We’re excited to share all the work from SAIL that will be presented, and you’ll find links to papers, videos and blogs below. Feel free to reach out to the contact authors directly to learn more about th…

Selective Classification Can Magnify Disparities Across Groups

Selective classification, where models are allowed to “abstain” when they are uncertain about a prediction, is a useful approach for deploying models in settings where errors are costly. For example, in medicine, model errors can have life-or-death ramifications, but abstentions can be easily handle…

Stanford AI Lab Papers at EMNLP/CoNLL 2021

The 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021) will take place next week, colocated with CoNLL 2021. We’re excited to share all the work from SAIL that will be presented, and you’ll find links to papers, videos and blogs below. Feel free to reach out to the cont…

Stanford AI Lab Papers at CoRL 2021

The Conference on Robot Learning (CoRL 2021) will take place next week. We’re excited to share all the work from SAIL that will be presented, and you’ll find links to papers, videos and blogs below. Feel free to reach out to the contact authors directly to learn more about the work that’s happening …

Stanford AI Lab Papers and Talks at NeurIPS 2021

The thirty-fifth Conference on Neural Information Processing Systems (NeurIPS) 2021 is being hosted virtually from Dec 6th – 14th. We’re excited to share all the work from SAIL that’s being presented at the main conference, at the Datasets and Benchmarks track and the various workshops, and yo…

BanditPAM: Almost Linear-Time k-medoids Clustering via Multi-Armed Bandits

TL;DR Want something better than (k)-means? Our state-of-the-art (k)-medoids algorithm from NeurIPS, BanditPAM, is now publicly available! (texttt{pip install banditpam}) and you’re good to go! Like the (k)-means problem, the (k)-medoids problem is a clustering problem in which our objective i…

Reward Isn’t Free: Supervising Robot Learning with Language and Video from the Web

This work was conducted as part of SAIL and CRFM. Deep learning has enabled improvements in the capabilities of robots on a range of problems such as grasping 1 and locomotion 2 in recent years. However, building the quintessential home robot that can perform a range of interactive tasks, from cooki…

How to Improve User Experience (and Behavior): Three Papers from Stanford’s Alexa Prize Team

Introduction In 2019, Stanford entered the Alexa Prize Socialbot Grand Challenge 3 for the first time, with its bot Chirpy Cardinal, which went on to win 2nd place in the competition. In our previous post, we discussed the technical structure of our socialbot and how developers can use our open-sour…

Stanford AI Lab Papers and Talks at AAAI 2022

The 36th AAAI Conference on Artificial Intelligence (AAAI 2022) is being hosted virtually from February 22th – March 1st. We’re excited to share all the work from SAIL that’s being presented, and you’ll find links to papers, videos and blogs below. Feel free to reach out to the contact authors…

Understanding Deep Learning Algorithms that Leverage Unlabeled Data, Part 1: Self-training

Deep models require a lot of training examples, but labeled data is difficult to obtain. This motivates an important line of research on leveraging unlabeled data, which is often more readily available. For example, large quantities of unlabeled image data can be obtained by crawling the web, wherea…

Grading Complex Interactive Coding Programs with Reinforcement Learning

[Summary] tl;dr: A tremendous amount of effort has been poured into training AI algorithms to competitively play games that computers have traditionally had trouble with, such as the retro games published by Atari, Go, DotA, and StarCraft II. The practical machine learning knowledge accumulated in d…

Discovering the systematic errors made by machine learning models

Discovering systematic errors with cross-modal embeddings In this blog post, we introduce Domino, a new approach for discovering systematic errors made by machine learning models. We also discuss a framework for quantitatively evaluating methods like Domino. Links: 📄 Paper (ICLR 2022) 🌍 Longer Walkt…

Stanford AI Lab Papers and Talks at ICLR 2022

The International Conference on Learning Representations (ICLR) 2022 is being hosted virtually from April 25th – April 29th. We’re excited to share all the work from SAIL that’s being presented, and you’ll find links to papers, videos and blogs below. Feel free to reach out to the contact auth…

Stanford AI Lab Papers and Talks at ACL 2022

The 60th Annual Meeting of the Association for Computational Linguistics (ACL) 2022 is taking place May 22nd – May 27th. We’re excited to share all the work from SAIL that’s being presented, and you’ll find links to papers, videos and blogs below. Feel free to reach out to the contact authors …

LinkBERT: Improving Language Model Training with Document Link

Language Model Pretraining Language models (LMs), like BERT 1 and the GPT series 2, achieve remarkable performance on many natural language processing (NLP) tasks. They are now the foundation of today’s NLP systems. 3 These models serve important roles in products and tools that we use every day, su…

14 Hidden Python Features for Beginners (Part- 1)

😊Here are some lesser-known but useful features of the Python for everyday use. 🐍 1. Merge Dictionaries >>> d1 = {“a”:1, “b”: 2}>>> d2 = {“c”:3, “d”:4}>>> dict(d1, **d2){’a’: 1, ‘b’: 2, ‘c’: 3, ‘d’: 4}>&g…

Bitcoin P2PKH Transaction Breakdown

The goal of this post is to give a thorough introduction to the most common type of Bitcoin transactions, Pay-to-Public-Key-Hash (P2PKH). To achieve this, the following is presented: A succinct overview of the concept of an unspent transaction output (UTXO) and how a transaction is formedA breakdown…

The World’s Most Pitiful Mining Rig

Originally written in January 2018 and reposted here. This was my first ever hardware build of any kind and was a great learning experience. Purpose Last year I considered mining but felt like it was “too late”. I deeply regret that decision and this past month I decided to rectify my mistake. I hav…

What data science is all about ??

What data science is all about ?? Data science is a buzz word these days. More and more people are making or planning to make a career switch to data science. Many institutes have mushroomed who claim to be the best and have fancy curriculum covering variety of algorithms. Some have taken it a step …

Machine Learning for Sales Forecast

Sales Forecasting is about estimating the sales that are yet to happen. Accurate sales forecast are essential for the success of any business. When done correctly, sales forecast can be used as an input to optimize several other business functions like manufacturing, inventory, supply chain, finance…

Understanding the Bitcoin Blockchain Header

The composition of the block header is an intricate and highly consequential process. If Bitcoin is a living, breathing organism, then the block header is the heart of the entire machine. The “block” in the Bitcoin blockchain is what moves and settles millions of dollars of value every 10 minutes an…

How I Keep Up with the Latest Innovations in AI and ML

Breaking down my reading list of what’s new in the AI world Image by Free-Photos from Pixabay The field of Machine Learning and Artificial Intelligence is changing rapidly. Five years ago, classical Machine Learning was the hottest trend; now it’s just like an iPhone 6S — outdated. Deep Learning dom…

Part 1: Taproot & Schnorr and its Impact on Mining

This is the first part of a two part blog post. Part 1 provides an overview of Bitcoin’s current signature scheme, an overview of Schnorr and Taproot, and an analysis of these upgrades from a miner’s perspective. Part 2 is a breakdown from a technical perspective so a reader can understand what this…

Part 2: Bitcoin P2TR Transaction Breakdown

This is the second part of a two part blog post. Part 1 gives an overview of Bitcoin’s current signature scheme, an overview of Schnorr and Taproot, and an analysis of these upgrades from a miner’s perspective. Part 2 is a breakdown from a technical perspective so a reader can understand what this a…

How the AI in Tactical Troops: Anthracite Shift handled teleportation mechanic

Tactical Troops: Anthracite Shift is a top-down, turn-based game that mixes tactical skills and the excitement of 80’s sci-fi movies. Created by QED Games Team of QED Software, it features many mechanics posing a great challenge for AI controlled characters, such as gridless movement and the topic o…

The Metric System: How to Correctly Measure Your Model

The deep dive into the world of model assessment metrics that you didn’t know you needed to know — until now The code used to generate the graphs and the KS Area Between Curves computation in this post is available as part of the dython library Image by lloorraa from Pixabay Here’s a classic scenari…

Can AI be easy as ABC?

Can AI be easy as ABC? Parents-developers explain Do you remember the infamous question: “So what do your parents do at work?”. If someone were to ask your children what their parents do at work, do you know what their answer will be? The area of artificial intelligence is generally difficult to def…

Nature-Inspired Algorithms

source: own work based on Todd Huffman from Phoenix, AZ, CC BY 2.0 <https://creativecommons.org/licenses/by/2.0>, via Wikimedia Commons by Maciej Świechowski “Look deep into nature, and then you will understand everything better” — Albert Einstein Since ancient times, nature has been serving a…

6 Papers Every Modern Data Scientist Must Read

A list of some of the most important modern fundamentals of Deep Learning everyone in the field show be familiar with Photo by 🇸🇮 Janko Ferlič on Unsplash Data Scientist, Machine Learning Expert, Algorithm Engineer, Deep Learning Researcher — whatever your title might be, if using advanced concepts …